Trace level detection of analytes using artificial olfactometry

ABSTRACT

The present invention provides methods for detecting the presence of an analyte indicative of various medical conditions, including halitosis, periodontal disease and other diseases are also disclosed.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Applications Ser.No. 60/090,012, filed Jun. 19, 1998, and Ser. No. 60/091,179, filed Jun.30, 1998, the disclosures of which are incorporated herein by referencein their entirety.

STATEMENT AS TO RIGHTS TO INVENTIONS MADE UNDER FEDERALLY SPONSOREDRESEARCH AND DEVELOPMENT

The research carried out in the subject application was sponsored, inpart, by grants from: ARO (E)AAG-55-97-1-0187); DARPA(DAAK60-97-K-9503); and NASA (49-244-30002-0-8280), and is subject tothe provisions of Public Law 96-517 (35 U.S.C. § 202). The governmentmay have certain rights in any patents issuing on this application.

BACKGROUND OF THE INVENTION

An artificial olfactory system is a device that is capable of detectinga wide variety of analytes in fluids such as vapors, gases and liquids.The device comprises an array of sensors that in the presence of ananalyte produces a response. The device produces a unique signatureoutput for a particular analyte. Using pattern recognition algorithms,the output signature, such as an electrical response, can be correlatedand compared to a particular analyte or mixture of substances that areknown. By comparing the unknown signature with the stored or knownsignatures, the analyte can be detected, identified and quantified.

There are many instances where it is desirable to measure trace amountsof analytes. However, in certain instances, the analytes are found atlevels that are too low to register a robust signal by direct exposureto currently available sensors. In headspace analysis of applications inagricultural, wine, tobacco, perfume, plastics, and the food industries,the detection and classification of trace levels of gases are present inthe sub part per million (ppm) range, making detection difficult.Moreover, in residue analysis of pesticides on crops, the trace levelsof certain herbicides must meet federal guidelines. For certain crops,these residues are present on the crops in the part per billion levels(ppb).

Another potential application wherein the detection of trace levels ofanalytes is important is the diagnosis of patients' conditions from ananalysis of their breath. Marker gases such as hydrogen sulfide andmethyl mercaptan, which are important in diagnosing the presence of oralor lung conditions from the breath of human patients, often exist inconcentrations of 0.01-1 parts per million (or lower). However, thethreshold detection levels of currently known sensors are in the rangeof 1-100 parts per million.

Currently, the most widely used device for detecting oral malodors isthe Halimeter, which is commercially available from Interscan Corp.(Chatsworth, Calif.). Using an electrochemical cell that is sensitive tovolatile sulfur compounds (VSC), the device can oxidize the VSC at theanode according to the following reactions:

H₂S→S+2H⁺+2e⁻

2CH₃—SH→CH₃—S—S—CH₃+S+2H⁺+2e⁻

CH₃—S—CH₃+2H₂O→2CH₃OH+S+2H⁺+2e⁻

However, one obvious drawback is that the Halimeter cannot distinguishbetween volatile sulfur compounds. Similarly, other volatile substancescan interfere with the readings of the VSC.

A second device for the detection of breath and odors associatedtherewith is based on zinc-oxide thin film semiconductor technology andhas recently been developed for measuring VSC (see, Shimura M et al., JPeriodontol. 67:396-402 (1994)). New Cosmos Electric Co. (Osaka, Japan)manufactures this device. This device, however, is limited because it issusceptible to interference from organic vapors unrelated to oralmalodor (see, Yaegaki K, In Rosenberg, “Bad Breath: ResearchPerspectives,” Proceedings of the First International Workshop on OralMalodor, Ramot Publishing, Tel Aviv University pp. 41-54 (1993)) 87-108(1995)).

Another analysis for breath detection is a test based on the enzymesubstrate benzoyl-DL-arginine-naphthylamine (BANA) (see, Loesche et al.,J. Clin. Microbiol. 28:1551-1559 (1991); and Loesche et al. JPeriodontol., 61:189-196 (1991)). This test is marketed under the brandname Peroscan and is available from Oral-B Laboratories (Redwood City,Calif.). Scrapings from the tongue, saliva, or plaque samples aredeposited directly on a reagent card. Following substrate addition, ablue spot develops if anaerobes are present. Studies have shown thatBANA results are not highly correlated with VSC measurements and thatthe test is often detecting other analytes (see, Kozlovsky et al., JDent. Res., 73: 103-1042 (1994)).

It has been estimated that at least 50% of the population suffers fromchronic oral malodor (see, Bosy, J. Can. Dent. Assoc. 63:196-201(1997)). A significant fraction of the population is worried about badbreath, even though there is usually no underlying disease (see, Iwakuraet al, J. Dent. Res. 7:1568-1574 1 (1994)). Food, of course, is anothercause of oral malodors. However, there are many people who have anunwarranted phobia of bad breath. The size of the market for breathfresheners, chewing gums, and mouth rinses is an indicator of thispropensity.

In addition to mammalian breath measurements, respiratory devices foranesthetic and respiratory gas mixtures must be monitored at very lowconcentrations of analytes. Medical devices mix the anesthetic withbreathing gas prior to delivery to the patient. In an anesthetic device,it is imperative that the concentration of the anesthetic, gas flow andamounts of the mixture and starting gases be known with certainty. Inmost instances, the anesthetic amounts are at very low concentrationlevels.

One approach to increase sensitivity to certain analytes is to useselective filters or membranes. For instance, U.S. Pat. No. 5,841,021,which issued to De Castro et al., discloses an electrochemical gassensor that has a catalytically active sensor electrode, a referenceelectrode and a permselective filter or membrane layer. The filter ismade of a material that provides for molecular specificity of certaingases, such as carbon monoxide. The membrane allows the sensors to beselective to the chemical analyte of interest. The filter only allowsthe analytes of interest to contact the sensor. By removing interferingsubstances through filtration, the sensor becomes more selective andthus sensitive to the analyte of interest.

In addition, U.S. Pat. No. 5,057,436, which issued to Ball, discloses amethod and apparatus for detection of toxic gases, such as ammonia,using a metal oxide semiconductor and an electrochemical sensor.Disposed between the two sensors is an absorber having an absorbent thatreacts with ammonia.

In view of the foregoing, what is needed in the art is a vaporconcentrator for an array of sensors, especially for an electronic nosesensor array. In addition, methods are needed to detect odors anddiagnose medical conditions. The present invention fulfills these andother needs.

SUMMARY OF THE INVENTION

In certain instances, it is desirable to measure trace amounts ofanalytes using sensor array technology. The present invention increasesthe sensitivity to such analytes by a large factor, and thus allows forthe use of existing sensor systems for applications where an increase insensitivity renders them more effective. As such, in certain aspects,the present invention provides a device for detecting the presence of ananalyte, the device comprising: a sample chamber having a fluid inletport for the influx of the analyte; a fluid concentrator in flowcommunication with the sample chamber, wherein the fluid concentratorhas an absorbent material capable of absorbing the analyte and capableof desorbing a concentrated analyte; and an array of sensors in fluidcommunication with the concentrated analyte. In certain preferredembodiments, the device further includes a detector operativelyassociated with each sensor that provides a response in the presence ofthe analyte.

The absorbent material of the fluid concentrator can be, but is notlimited to, a nanoporous material, a microporous material, a chemicallyreactive material, a nonporous material and combinations thereof Incertain instances, the absorbent material can concentrate the analyte bya factor that exceeds a factor of about 10⁵, and more preferably by afactor of about 10² to about 10⁴. Using the device of the presentinvention, the analyte can be concentrated from an initial sample volumeof about 10 liters and then desorbed into a concentrated volume of about10 milliliters or less, before being presented to the sensor array.

In another embodiment, removal of background water vapor is conducted inconjunction, such as concomitantly, with the concentration of theanalyte. Once the analyte is concentrated, it can be desorbed using avariety of techniques, such as heating, purging, stripping, pressuringor a combination thereof

In yet another aspect, the present invention provides methods fordetecting or diagnosing, for example, infections, lung cancer, oralinfections and halitosis using a breath sample of a mammal. Preferably,the mammal is a human being. In other embodiments, the present inventionprovides methods for other medical applications, such as those involvingthe detection of marker gas(es) in mammalian breath as well as odorsfrom potentially infected areas of the skin.

In still yet another aspect, the present invention provides methods anddevices for the process control of anesthetic gases of clinicalinterest. Using the apparatus of the present invention, monitoring andquantitating anesthetics is readily accomplished.

These and other embodiments and advantages will be readily apparent whenread with the accompany drawings and the detailed description of theinvention which follows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a cross-sectional view of a breath collector and concentratorof the present invention.

FIG. 2 is a cross-sectional view of a breath collector and concentratorof the present invention.

FIG. 3 is a head space analyzer of the present invention.

FIG. 4 is a block diagram of a vaporizing system of the presentinvention.

FIGS. 5A and 5B illustrate various response patterns obtained using thedevices of the present invention. Panel A illustrates the responses of32 sensors to anerobius (Bac1), gingivalis (Bac2) and a control; Panel Billustrates responses of 32 sensors to anerobius (Bac1), gingivalis(Bac2) and a control (Expanded y-axis).

FIG. 6 illustrates the results of principle component analysis on a dataset of Ps anerobius (Bac1) and P gingivalis bacteria (Bac2) plus thecontrol (the medium in which the bacteria were grown).

FIG. 7 illustrates the response of sensors in the presence of 3 percenthalothane.

FIG. 8 illustrates the results of the response of sensor array in thepresence of halothane.

DETAILED DESCRIPTION OF THE INVENTION AND PREFERRED EMBODIMENTS I. TheDevice

In one aspect, the present invention allows existing sensor systems tobe more effective and efficient by providing enhancements in thedetection sensitivity to trace analytes. As such, in one embodiment, thepresent invention provides a device for detecting the presence of ananalyte in a fluid, comprising:

a) a sample chamber having a fluid inlet port for the influx of theanalyte;

b) a fluid concentrator in flow communication with the sample chamber,the fluid concentrator having an absorbent material capable of absorbingthe analyte and capable of desorbing a concentrated analyte; and

c) an array of sensors in fluid communication with the concentratedanalyte.

In preferred embodiments, the device further comprising a detectoroperatively associated with each sensor that provides a response in thepresence of an analyte. In certain embodiments, the sample chamber isdesigned for the collection of mammalian breath. Under certainconditions, mammalian breath contains marker gases indicative of certaininfections, disorders and medical conditions and the devices of thepresent invention can be used to detect such marker gases. In certainaspects, the sample chamber is a breath collector and concentrator (BCC)and is fabricated to collect the breath of a mammal. Preferably, themammal is a human being, although the BCC can be fabricated to collectthe breath of other mammals such as cows, sheep, horses, dogs, cats,hogs, etc. The BCC is convenient to use and in certain instances is aportable handheld device with a suitable handle portion for convenientuse.

With reference to FIG. 1, in certain embodiments, the sample chamber isa cylindrical reservoir having an inlet port (10) for the influx of gas,such as breath, and an outlet port (19) for the exhaust of breath. TheBCC has a first end and a second end. The cylindrical container (12)extends between the first end and the second end, and the cylindricalcontainer has an open interior chamber (13).

The first end of the body is open for access to the interior chamber andfunctions as a breath inlet port and is vented by a breath exhaust. Thebreath inlet port optionally contains a disposable adapter for multipleuse. A concentrator portal (14) opens into the interior chamber and isin flow communication with the fluid concentrator. The fluidconcentrator (15) comprises an absorbent material capable of absorbingthe analyte and capable of desorbing a concentrated analyte. In certainembodiments, valves control the breath flow so the sample of breathwithin the chamber can be directed to the fluid concentrator. The fluidconcentrator optionally contains a second exhaust or exit port.

A valve (16) is mounted anterior to the outlet port with sufficientforce to maintain the vent closed except when the mammal is exhalinginto the chamber. Optionally, the fluid concentrator is jacketed (17)with a heater for the purpose of desorbing a concentrated analyte. Asillustrated in FIG. 1, the BCC has a sensor array portal (18) that opensinto the interior chamber and is in fluid communication with thedesorbed concentrated analyte and the sensor array (11). In certainembodiments, the sensor array is disposed downstream of the inlet portand the concentrator portal. In other embodiments, the sensor array isdisposed between the inlet port and the concentrator portal (not shown).In certain embodiments, the BCC has an adapter to provide breath fromthe nostril(s) to avoid cross-contamination from the mouth.

In certain aspects, the BCC can be a desktop model. As illustrated inFIG. 2, the first end (24) of the BCC (20) is open for access to theinterior chamber (22) and functions as a breath inlet port and is ventedby a breath exhaust (25). A fluid concentrator (23) opens into theinterior chamber (27) and is in flow communication (28) with the breathexhaust (25). In this embodiment, the breath is circulated through thechamber using a fan (21). The sensor array (26) is in flow communicationwith the desorbed analyte.

In various embodiments, the fluid concentrator can be disposed withinthe sample chamber or outside the sample chamber. In addition, thesensor array can be disposed within the sample chamber or outside thesample chamber. Moreover, the sensor array can be configured to beexternal from the BCC and to extend into the mouth or nasal cavity. Thepresent invention embodies all such variations.

Although the device of FIG. 1 is shown as a handheld breath collectorand concentrator, those of skill in the art will appreciate that incertain other embodiments, the device and methods of the presentinvention can be adapted and configured to detect within or aroundvarious other areas of interest including, but not limited to, mucousmembranes, nose, nasal passages, eye, skin, ear, inner ear, mouth,tongue, throat, colon, duodenum, body cavities, stomach, vagina andpenis. Moreover, the device and methods of the present invention can beconfigured to detect all body fluids including, but not limited to,urine, perspiration, tears, blood, mucus, pus, salvia, feces,menstruation fluid, sperm, eggs, spinal fluid and mammary glanddischarge.

In another embodiment, the sample chamber is a head space analyzer (HSA)and can be fabricated from an inert material, such as a moldedfiberglass, or in certain embodiments can be fabricated from plastic andcan be configured like a box. As illustrated in FIG. 3, the samplechamber (32) optionally has a glass-viewing window and the box cancontain pressure and temperature gauges (37) to allow pressure andtemperature monitoring. Moreover, the sample chamber optionally containsvalves for gas input and exhaust of the box. Optionally, the samplechamber comprises a heater and a pressure control means for aninternally controlled atmosphere.

Similar to the BCC, the HSA has a first end (34) that is open for accessto the interior chamber (32) and functions as an inlet port (30) and isvented by an exhaust (35). A fluid concentrator (33) is disposed outsidethe sample chamber and is in flow communication (36) with the exhaust(35). The sensor array (39) is in flow communication with the desorbedanalyte.

Optionally, the HSA contains appropriate connections for high throughputscreening (HTS). High throughput screening includes a robotic armaturesystem. In general, these systems include automated workstations likethe automated apparatus developed by Takeda Chemical Industries, LTD.(Osaka, Japan) and many robotic systems utilizing robotic arms (ZymateII, Zymark Corporation, Hopkinton, MA.; Orca, Hewlett-Packard, PaloAlto, Calif.), which mimic the manual operations performed by atechnician. The nature and implementation of modifications to thesedevices (if any) so that they can operate will be apparent to personsskilled in the relevant art.

In operation, a volume of the gas to be sampled, such as human breath,is introduced into a sample chamber where it is transported by means ofconvention into the vicinity of the sorbent material. Suitabletransporting means include, but are not limited to, a fan, an air pump,or it can be means for heating the cylindrical container (12) to createa convective air flow between the inlet and the outlet. The sorbentmaterial is chosen from known materials designed for the purpose ofsorbing gases, vapors, and the like. In certain embodiments, the sorbentmaterial includes, but is not limited to, a nanoporous material, amicroporous material, a chemically reactive material, a nonporousmaterial and combinations thereof Such absorbents include, for example,activated carbon, silica gel, activated alumina, molecular sieve carbon,molecular sieve zeolites, silicalite, AIPO₄, a polymer, a co-polymer,alumina and mixtures thereof In certain embodiments, the absorbent has apore size from about 1 nm to about 100 nm and, preferably, from about 1nm to about 50 nm.

Suitable commercially available adsorbent materials are disclosed inU.S. patent application Ser. No. 09/271873, filed Mar. 18, 1999, andinclude, but are not limited to, Tenax TA, Tenax GR, Carbotrap,Carbopack B and C, Carbotrap C, Carboxen, Carbosieve SIII, Porapak,Spherocarb, and combinations thereof. Preferred adsorbent combinationsinclude, but are not limited to, Tenax GR and Carbopack B; Carbopack Band Carbosieve SIII; and Carbopack C and Carbopack B and Carbosieve SIIIor Carboxen 1000. Those skilled in the art will know of other suitableabsorbent materials.

After sometime period that is chosen to be adequate for sorbing thedesired analytes from the vapor phase onto the material, the circulationis stopped and then the material is desorbed from the sorbent phase andreleased into the sensor chamber. The desorbing of the concentratedanalyte for the sorbent can be by accomplished by thermal means,mechanical means or a combination thereof. Desorption methods include,but are not limited to, heating, purging, stripping, pressuring or acombination thereof

In certain embodiments, the sample concentrator is wrapped with a wirethrough which current can be applied to heat and thus, desorb theconcentrated analyte. The analyte is thereafter transferred to thesensor array.

The process of sorbing the material onto the sorbent phase not only canbe used to concentrate the material, but also can be advantageously usedto remove water vapor. The water vapor is preferably removed prior toconcentrating the analyte; however, in various embodiments, the vaporcan be removed concomitantly or after the analyte is concentrated. In apreferred embodiment, the water vapor is removed prior to presenting thedesired analyte gas mixture to the sensor array. Thus, in certainembodiments, the fluid concentrator contains additional absorbentmaterial to not only concentrate the analyte, but to remove unwantedmaterials such gas contaminates and moisture.

In certain instances and depending on the absorbent used, theconcentration factor can exceed a factor of 10⁵, and more preferably bya factor of about 10² to about 10⁴ Thus, the analyte gases can beconcentrated from an initial sample volume of about 10 liters and thendesorbed into a volume of about 10 milliliters or less when they arepresented to the sensor array.

The array of sensors is present in fluid communication with theconcentrated analyte. Various sensors suitable for detection of analytesinclude, but are not limited to: surface acoustic wave (SAW) sensors;quartz microbalance sensors; conductive composites; chemiresitors; metaloxide gas sensors, such as tin oxide gas sensors; organic gas sensors;metal oxide field effect transistor (MOSFET); piezoelectric devices;infrared sensors; temperature sensors, humidity sensors, sintered metaloxide sensors; Pd-gate MOSFET; metal FET structures; metal oxidesensors, such as a Tuguchi gas sensors; phthalocyanine sensors;electrochemical cells; conducting polymer sensors; catalytic gassensors; organic semiconducting gas sensors; solid electrolyte gassensors; piezoelectric quartz crystal sensors; dye-impregnated polymerfilms on fiber optic detectors; polymer-coated micromirrors;electrochemical gas detectors; chemically sensitive field-effecttransistors; carbon black-polymer composite chemiresistors;micro-electro-mechanical system devices; andmicro-opto-electro-mechanical system devices and Langmuir-Blodgett filmsensors.

In a preferred embodiment, the sensors used in the present invention aredisclosed in U.S. Pat. No. 5,571,401, which is incorporated herein byreference. Briefly, the sensors described therein are conductingmaterials and nonconducting materials arranged in a matrix of conductingand nonconducting regions. The nonconductive material can be anonconducting polymer such as polystyrene. The conductive material canbe a conducting polymer, carbon black, an inorganic conductor and thelike. The sensor arrays comprise at least two sensors, typically about32 sensors, and in certain instances 1000 or more sensors up to about10⁶ sensors. In a preferred embodiment, at least two sensors arecompositionally different. The array of sensors can be formed on anintegrated circuit using semiconductor technology methods, an example ofwhich is disclosed in PCT Patent Publication No. WO99/08105, entitled“Techniques and Systems for Analyte Detection,” published Feb. 19, 1999,and incorporate herein by reference. Another preferred sensor system isdisclosed in PCT Patent Publication No. WO99/27357, published Jun. 6,1999.

In certain embodiments, the temporal response of each sensor (responseas a function of time) is recorded and can be displayed. Variousresponses include, but are not limited to, resistance, impedance,capacitance, inductance, magnetic, optical, etc. The temporal responseof each sensor can be normalized to a maximum percent increase andpercent decrease that produces a response pattern associated with theexposure of the analyte. By iterative profiling of known analytes, astructure-function database correlating analytes and response profilesis generated. Unknown analytes can then be characterized or identifiedusing response pattern comparison and recognition algorithms.Accordingly, analyte detection systems comprising sensor arrays, ameasuring device for detecting responses across each sensor, a computer,a display, a data structure of sensor array response profiles, and acomparison algorithm(s) or comparison tables are provided. In anotherembodiment, the electrical measuring device or detector is an integratedcircuit comprising neural network-based hardware and a digital-analogconverter (DAC) multiplexed to each sensor, or a plurality of DACs, eachconnected to different sensor(s).

In certain embodiments, a method for using the sensors for detecting thepresence of an analyte in a fluid involves sensing the presence of ananalyte in a fluid with a chemical sensor comprising first and secondconductive leads electrically coupled to and separated by a chemicallysensitive sensor as described above by measuring a first responsebetween the conductive leads when the sensor is contacted with a firstfluid comprising an analyte at a first concentration and a seconddifferent response when the sensor is contacted with a second fluidcomprising the analyte at a second different concentration. As discussedabove, suitable responses include, but are not limited to, resistance,impedance, capacitance, inductance, magnetic, optical, etc.

II. Medical Applications

The methods and apparatus of the present invention are extremely usefuland can be advantageously used for the detection, identification, andclassification of trace gas components, and are extremely useful in avariety of applications, including medical applications. In certainaspects, the methods and devices of the present invention are useful andvery effective for the detection and diagnosis of diseases. In general,certain volatile marker gas (es) characterizes the detection ordiagnosis of a disease state or medical condition. The methods andapparatus of the present invention can advantageously by used to detectvolatile marker gases and compounds indicative of medical conditions,disease processes, infections, illness and well-being. Using thesemarker gases and compounds, clinicians can use the diagnosticinstruments and methods of t he present invention to make diagnoses andformulate appropriate treatments. The methods as described canoptionally be performed using a fluid concentrator as described herein.

A. Oral infections

In certain aspects, the present invention is extremely useful for thedetection of infections, such as oral infections and dental cares. Forexample, bacteria cause two widespread dental problems—halitosis andperiodontal disease—and, as disclosed herein, the methods and apparatusof the present invention can detect the off-gases produced by suchbacteria.

1. Halitosis

Halitosis is caused by the breakdown of proteins by microbes on the backof the tongue. The tongue coating is comprised of epithelial cells fromthe oral mucosa, leukocytes from periodontal pockets, andmicroorganisms. While the mouth is resident to over 300 bacterialspecies (see, Loesche et al., In Rosenberg M., Editor, “Bad Breath:Research Perspectives,” Proceedings of the First International Workshopon Oral Malodor, Ramot Publishing, Tel Aviv University pp. 41-54(1993)), the relative size of each population is a function of manyfactors. Bad breath has been associated with the expansion of anaerobicspecies (see, Loesche et al., In Rosenberg Ed., “Bad Breath: ResearchPerspectives,” Proceedings of the First International Workshop on OralMalodor, Ramot Publishing, Tel Aviv University pp. 41-54 (1993); deBoveri HE et al., J. Am. Dent. Assoc., 126:1384-1393 (1995)). Theunderlying cause of the increase in anaerobes can be poor oral hygiene,aging, deep crevices in the tongue, post-nasal drip, or numerous otherconditions.

The chemical markers of bad breath have been identified and include, butare not limited to, volatile sulfur compounds (VSC) (see, Richter etal., Arch. Oral Biol., 9:47-53 (1964); Tonzetics Arch. Oral Biol.,16:587-597 (1971); Tonzetich, J. Periodontol. 48:13-20 (1977); TonztichJ, J. Int. Dent. J. 28:309-319 (1978); and Tonzetich, Arch. Oral Biol.,16:587-597 (1971)).

As such, the present invention provides a method for the detection ofhalitosis, the method comprising: contacting an array of sensors withmammalian breath suspected of containing a marker gas indicative ofhalitosis; and detecting the marker gas to determine the presence ofhalitosis. In preferred embodiments, the marker gases being detected bythe sensors are volatile sulfur compounds.

2. Periodontal Disease

A far more serious consequence of oral infections is periodontaldisease. Gingivitis is the inflammation of the gums and periodontitis iswhen the gum infection damages the bone and supporting tissues. Theseconditions are the result of the expansion of certain species ofbacteria. If a piece of food is trapped between the teeth, the bacterialtypes that can utilize the various nutrients present will multiply. Inaddition, some of their metabolic products can give rise to a secondarray of organisms. And finally, if the population explosion of bacteriais sufficient to elicit an inflammatory response, a third wave ofbacteria can arise that prefers the gingival crevicular fluid (see,Loesche W J et al., In Rosenberg, Bad Breath Research Perspectives,Ramot Publishing, Tel Aviv, pp. 41-54 (1993)).

VSC are also an indicator of periodontal disease (see, Loesche et al.,In Rosenberg, BadBreath: Research Perspectives, Ramat Publishing, TelAviv, (1995); Yaegaki et al., J. Periodontia. Res. 27:233-238 (1992);Tonzetich et al., J. Dent. Res 58:175 (1979); Frostell et al., Dent. J.20:436-450 (1970); Sato et al., Bull. Tokyo Dent. Coll., 21:171-178(1980); Kostelc et al, J. PeriodontalRes. 15:185-192 (1980)). Inaddition, a number of other compounds can be indicative of variousbacterial populations (see, Bosy et al., J. Periodontal. 65:3746 (1994);McCulloch et al., In Rosenberg, Bad Breath Research Perspectives, RamatPublishing, Tel Aviv, pp. 109-117 (1995)).

A significant development in recent years has been the use ofanti-microbials to treat periodontitis instead of surgery. It has beenshown that 80% of patients scheduled for surgery or extractions could besuccessfully treated with a course of metronidazole, doxycycline, orchlorhecidine. Overall, only about 10% of the teeth required theconventional surgery or extraction. Surprisingly, by using the apparatusof the present invention, it is possible to make a quick diagnosis,thereby alleviating unnecessary surgery.

As such, the methods and apparatus of the present invention can be usedfor the detection of periodontal disease. Thus, the present inventionprovides a method for the detection of periodontal disease, the methodcomprising: contacting an array of sensors with mammalian breathsuspected of containing a marker gas indicative of periodontal disease;and detecting the marker gas to determine the presence of periodontaldisease. As explained above, and detailed hereinbelow, numerous markergases can be used to detect and evaluate the severity of periodontaldisease.

B. Pneumonia Detection

In certain instances, it currently takes two to three days to culturethe bacteria and determine whether the species that cause pneumonia arepresent. Often, rather than waiting for this determination, medicalpersonnel prescribe broad-spectrum antibiotics. Unfortunately, thisprophylactic procedure can promote the emergence of antibiotic-resistantstrains.

The methods and devices of the present invention can alleviate theunnecessary prescribing of antibiotic(s) by providing rapid accuratedetection and diagnosis of bacteria attributable to pneumonia. Thus, thepresent invention provides a method for the detection of pneumonia, themethod comprising: contacting an array of sensors with mammalian breathsuspected of containing a marker gases indicative of pneumonia; anddetecting the marker gas to determine the presence of pneumonia.

C. Wound Healing One of the major reasons for slow healing wounds can bea high level of bacteria. Frequently, wound healing is largelyundetected due to lack of tests for detecting microorganisms. Slow woundhealing is a problem that effects more than a million people each yearand costs billions of dollars to treat. Unfortunately, one of thestandard techniques of wound assessment is to smell the exudate on thedressing. Nurses are advised to be aware of a “repulsive” odor that maybe associated with necrotic tissue and “acrid or putrid” smells that areassociated with anaerobic bacteria.

However, these methods suffer from lack of specificity. While theabsence of odor is indicative of a clean wound, the presence of odordoes not necessarily signal an infection The switch in recent years tomoisture-retaining “wet dressings” has further complicated the problemof wound assessment. Most dressings have strong odors, but often timesthe odor is due entirely to the materials in the dressings.

While there is a quantitative culture methodology that can be employedto eliminate human errors, it is very expensive and time consuming Assuch, it is only used routinely in burn centers where patients are inmuch more serious conditions. Advantageously, the present inventionprovides a method for diagnosing wound healing comprising: contactingthe vapors associated with the wound with an array of sensors, therebyassessing the wound healing process.

D. Vaginitis

The vaginal discharge of women with bacterial vaginitis often has aprominent fishy odor. The presence of methylamine, isobutylamine,putrescine, cadaverine, histamine, tyramine, and phenethylamine aremarker gases of vaginitis (see, Brand et al., Obstetrics and Gynecology,68, 682-685 (1985)). Thus, the present invention provides a method forthe detection of vaginitis, the method comprising: contacting an arrayof sensors with vaginal vapors or discharge suspected of containing amarker gas indicative of vaginitis; and detecting the marker gas todetermine the presence of vaginitis.

E. Fertility

In yet another aspect, the present invention provides methods andapparatus for the detection of ovulation. The fertile period of a femalemammal, such as a human being, can be detected by measuring axillarysecretions. The markers are androstenol and/or dehydroepiandrosteronesulfate. Thus, the present invention provides a method for detectingovulation, the method comprising: contacting an array of sensors withvaginal vapor for the presence of a marker gas indicative of ovulation;and detecting the marker gas to determine ovulation.

F. OTHER APPLICATIONS

In addition to the foregoing applications, other applications for themethods and devices of the present invention include, but are notlimited to, environmental toxicology, remediation, biomedicine, materialquality control, food monitoring, agricultural monitoring, heavyindustrial manufacturing, ambient air monitoring, worker protection,emissions control, product quality testing, oil/gas petrochemicalapplications, combustible gas detection, H₂S monitoring, hazardous leakdetection, emergency response and law enforcement applications,explosives detection, utility and power applications,food/beverage/agriculture applications, freshness detection, fruitripening control, fermentation process monitoring and control, flavorcomposition and identification, product quality and identification,refrigerant and fumigant detection, cosmetic/perfume applications,fragrance formulation, chemical/plastics/pharmaceuticals applications,fugitive emission identification, solvent recovery effectiveness,hospital/medical applications, anesthesia and sterilization gasdetection, infectious disease detection, breath analysis and body fluidsanalysis.

Various other medical conditions and associated pathogens are set forthin Table 1

TABLE 1 INFECTIONS AND PATHOGENS Area of Infection Pathogen InterestAcute sinusitis Strep. pneumoniae, H. flu, Sinus Moraxella catarrhais,Group A strep., G(+) anaerobes, Staph. aureus Pharyngitis Group A, C, Gstrep. Pharynx Pneumonia Strep. pneumoniae, Lungs Mycoplasma, Chlamydiapneumoniae, H. flu Bronchitis Strep. pneumoniae, H. Flu, Lungs MoraxellaAmerican Thoracic Strep. pneumoniae, H. Lung Society (ATS) Class III CAPinfluenzae, Klebsiella, Staph. Severe CAP aureus, Legionella Sp., ATSClass IV-ICU Pseudomonas aerug., other gram-negative bacteria; Strep.pneumoniae, Staph. aureus, Legionella Sp., Pseudomonas aerug., othergram negative bacteria Cystitis in females; Enterobacteriaceae; UrinaryPyelonephritis; Prostatitis or Enterobacteriaceae & TractEpididymoorchitis Enterococcus sp. Acute Meningitis Hemophilusinfluenzae, CNS Meningitis(post surgical); Pneumococci, N. meningitidisBrain abscess Staphylococcus sp., gram- negative bacteria; Streptococcussp., anaerobes, Staph. sp Biliary tract; Peritonitis orEnterobacteriaceae, Abdomen Diverticular abscess Enterococcus sp.,anaerobes Cellulitis; Lymphangitis Streptococcus sp., Skin Cat bite, Dogbite, Decubitus Staphylococcus sp.; Pasturella ulcers,(uncomplicated) ormulticida, Staph & Strep., Diabetic foot ulcer anaerobes; Gram negative(uncomplicated); Toxic Shock bacteria; Gram-positive bacteria; AnaerobesEndometritis/Endomyometritis Enterobacteriaceae, Pelvis PelvicInflammatory Disease; Chlamydia sp., Streptococcus SepticThrombophlebitis sp. (group B Streptococcus), (postpartum) Neiserriagonorrhoeae Endocarditis (IE) Streptococci sp. Heart Prosthetic valveStaphylococcus sp. Staphylococcus epi. Septic arthritis, ProstheticStaphylococcus sp. & Strep. Bone & joint, Osteomyelitis sp., Neisseriagonorrhoeae, Joint Staphylococcus sp., Staphylococcus sp., Staph &Strep. sp., Enterobacteriaceae, anaerobes

G. Markers

As explained above, volatile sulfur compounds (e.g., H₂S, CH₃—SH,CH₃—S—CH₃) are the marker gases implicated in galitosis and periodontaldiseases (see, Tonzetich, Arch. Oral Biol., 16:587-597 (1971); Rizzo,Periodontics, 5:233 14 236 (1967)). Other analytes that have been shownto correlate with such clinical findings include, but are not limitedto, volatile organic acids (VOA), indole/skatole (indole), and diamines(see, Goldberg et al., J. Dent. Res., 73:1168-1172 (1994); Goldberg etal., In Rosesberg M Bad Breath Research Perspectives, Ramat Publishing,Tel Aviv, pp. 71-85 (1995)).

In addition, several other analytes have been reported to be associatedwith oral infections including pyridines/picolines (see, Kostelc et al.,J. Periodont. Res., 15:185-192 (1981); Kostelc et al., Clin. Chem.,27:842-845 (1981)). Overall, more than 80 volatile compounds have beenshown to be associated with saliva or tongue scrapings (see, Claus etal., J. High Resol. Chromatogr., 20:94-98 (1997)) and the methods andapparatus of the present invention can be used to advantageously detectsuch marker compounds and gases.

Using the methods and apparatus of the present invention it is alsopossible to detect the off-gasses associated with bacteria associatedwith oral maladies including, but not limited to, Prevotella intermedia;Fusobacterium nucleatum; Porphyromonas gingivalis; Porphyromonasendodontalis; Prevotella loescheii; Hemophilus parainfluenzae;Stomatococcus muci; Treponema denticola; Veillonella species;Peptostreptococcus anaerobius; Micros prevotii; Eubacterium limosum;Centipeda periodontii; Selemonad aremidis; Eubacterium species;Bacteriodes species; Fusobacterium periodonticum; Prevotellamelaninogenica; Klebsiella pneumoniae; Enterobacter cloacae; Citrobactersecies and Stomatococcus mucilaginus.

Moreover, a wide variety of analytes and fluids can be detected andanalyzed using the disclosed sensors arrays and electronic noses so longas the subject analyte(s) and fluids are capable of generating adifferential response across a plurality of sensors of the array.Analyte applications include broad ranges of chemical classes including,but not limited to, organics such as alkanes, alkenes, alkynes, dienes,alicyclic hydrocarbons, arenes, alcohols, ethers, ketones, aldehydes,carbonyls, carbanions, polynuclear aromatics and derivatives of suchorganics, e.g., halide derivatives, etc.; biomolecules such as sugars,isoprenes and isoprenoids; VOC; VOA; indoles; skatoles; diamines;pyridines; picolines; fatty acids; and derivatives of the forgoing, etc.

In addition to breath, the sensor arrays of the present invention can beused to identify various analytes in other biological fluids. Thesefluids include, but are not limited to, urine, perspiration, tears,blood, mucus, pus, salvia, feces, menstruation fluid, sperm, eggs,spinal fluid and mammary gland discharge.

In general, most conditions and diseases listed herein havemicroorganisms associated with them. The presence of marker gases andcompounds associated with the microorganism is in turn, indicative ofthe presence of the disease or condition. In a preferred embodiment, theoff-gas of the microorganism is the marker that is detected by methodsand devices of the present invention.

III. ANESTHETICS

In certain anesthetic vaporizers, a carrier gas, such as air, oxygen ornitrous oxide, is divided between a first stream directed to a chamber,wherein an anesthetic liquid is resident and a second stream or bypassstream. The first and second streams are recombined before delivery tothe patient. Another version of an anesthetic vaporizer is embodied in adevice wherein the anesthetic agent is injected directly into thecarrier gas stream.

In either instance, it is imperative that the concentration of volatileanesthetic liquid be known. The present invention provides methods andan apparatus for the process control of anesthetic gases. Using themethods and apparatus of the present invention, a fluid concentrator isoptionally used when monitoring and quantitating anestheticconcentration.

By using the apparatus and sensors described herein, it is possible todetect and quantitate the concentration of volatile anestheticsincluding, but not limited to, halothane, isoflurane, servoflurane,desflurane and enflurane. As such, the present invention provides ananesthetic vaporizing system for quantitating the concentration of theanesthetic, comprising: a carrier gas source for delivering a carriergas stream to a bypass valve, wherein the bypass valve splits thecarrier gas stream into a first carrier gas stream for delivery to aninlet port and a second carrier gas stream for delivery to a joiningvalve;

a vaporizing chamber for an anesthetic agent, comprising the inlet port,an outlet port, a vaporizing means and a conduit for delivery ofvaporized anesthetic from the outlet port to the joining valve; and

an array of sensors in flow communication with the joining valve toquantitate the anesthetic. In preferred embodiments, the system furthercomprising a detector operatively associated with each sensor thatprovides a response in the presence of an anesthetic vapor.

With reference to FIG. 4, the carrier gas source (41) delivers thecarrier gas to a bypass valve (44), wherein the carrier gas is splitbetween a first carrier gas stream for delivery to the inlet port (45)of the anesthetic vaporizer (40) and a second carrier gas stream whichconnects to a joining valve (46). The anesthetic vaporizer contains avaporizing means, such as a heater, pressure souce or aspirator (48).The vaporizer includes an outlet port (42) for delivery of the vaporizedanesthetic through a conduit (43) to the joining valve. The sensor array(49) is in flow communication with the joining valve.

The present invention also provides a method of quantitating ananesthetic vapor, comprising: containing the anesthetic vapor with asensor array to produce a response; detecting the response with adetector, thereby quantitating the anesthetic vapor.

The following examples are meant to illustrate and not limit the presentinvention.

IV. EXAMPLES Example 1

In this Example, the detection and identification of bacteria wasconducted by measuring the metabolic products produced from platebacteria cultures carried out using an electronic nose (a 32-sensorarray) and a Fisher Linear Discrimination (FLD) algorithm.

As shown herein, the data was also examined using principal componentanalysis (PCA) and statistical isolinear multicategory analysis (SIMCA).The results carried out on two very distinct bacteria, i.e.,peptostreplococcus anerobius and porphyromonas gingivalis, show that thetwo bacteria were clearly discriminated by the sensors as shown by PCA.The metabolites of additional an 11 bacteria and one fungus pluscontrols were tested and the data was examined using PCA, SIMCA and FLDand discrimination among the bacteria was demonstrated.

The objective of these experiments was to evaluate the discriminatingcapability of a thirty-two sensor array composed of mixtures of polymersand carbon black for metabolites produced by a variety of bacteria.Fourteen fresh cultures were tested for the 20 most commonly suspectedmalodor producing, oral and pharyngeal anaerobic and facultativebacteria including a fungus using a 32-sensor array. The experiment wasdone in two phases. The first phase consisted of testing two verydistinct bacteria, peptostreptococcus anerobius and porphyromonasgingivalis, plus a control (the media in which the bacteria wereindependently grown). Four sample tubes of each bacterium and thecontrol were tested to investigate reproducibility. The results from thefirst test indicated that gingivalis and anerobius could bediscriminated from each other and the control using a sensor arraydiscussed herein.

Ten samples of eleven bacteria, a fungus and ten controls were testedwith the same sensor array used described above. Table 3 lists thebacteria plus the main metabolite known to be produced by thesebacteria. Various statistical and mathematical techniques were used toanalyze the data obtained with chemiresistors on these microorganisms.One of the methods used to classify the metabolites produced from thevarious bacteria was principal component analysis, an unsupervisedpattern recognition technique. PCA transforms multidimensional data setsinto a lower dimensional graphical representation, which describes amajority of the variation in a data set. PCA defines a new set of axesto plot the samples, they are constructed so that a maximum amount ofvariation is described with a minimum number of axes, and the data ishence readily visualized in this transformed data space (see, K. R.Beebe, R. J. Pell, M. B. Seasholtz, Chemometrics: A Practical Guide,Wiley, New York, 1998.)

Another algorithm used to analyze the data set was Fisher LinearDiscrimination (FLD). FLD seeks a linear combination of the variables,which maximizes the ratio of its between-group variance to itswithin-group variance (see, B. D. Ripley, Pattern Recognition and NeuralNetworks, University Press, Cambridge, 1996, Chapter 3, p 93.).

Other algorithms used to analyze the data were K-nearest neighbor (KNN)and statistical isolinear multicategory analysis, SIMCA. Both of thesealgorithms are supervised pattern recognition methods used forpredicting the class of unknown samples given a training set of sampleswith known class membership. With KNN, a classification is always made,whether or not the unknown is a member of the class in the training set.KNN is a much simpler algorithm than SIMCA because unlike SIMCA it makesno assumptions about the size or shape of the class. SIMCA can detect ifan unknown sample is not a member of any class in the training set.SIMCA uses the shape and position of the object formed by the samples ina class for class definition (see, K. R. Beebe, R. J. Pell, M. B.Seasholtz, Chemometrics: A Practical Guide, Wiley, New York, 1998). Theresults obtained using all the described algorithms are set forth below.

A. EXPERIMENTAL

1. Testing Protocol

Thirty polymers were chosen based both on structural differences and onsolubility to generate a thirty two sensor array. The testing protocolused for all the bacteria was the same and is described below. Anerobiusand gingivalis were tested in one day, whereas the rest of the bacteriawere tested over several days.

Testing instrument: A Keithley electrometer and scanner were used toscan the resistances of 32 sensors during the experiment.

Sampling: the headspace above the bacteria was sampled using nitrogengas as the carrier. The flow rate used was 100 mL/minute. No dilutionwith air was done. The flow rate of the background air used to purge thesensors was 10 L/minute. No preconcentration was preformed.

Temperature: The temperature of the substrates was not controlled andthe measurements were done at room temperature for the first phasestudy. The temperature of the substrates was maintained at 28+0.1° C.for the second phase study.

Purge and Exposure times: For each sample test, there were 60 seconds ofbackground recording (purged with air), 120 seconds of exposure time,120 seconds of recovery time (purged with air with RH level of about3%), 180 seconds of recovery without recording the data (purged withair), and 30 seconds of final recording time (purged with air).

B. RESULTS AND DISCUSSION

1. Sensor Array Response

The response pattern of the 32-sensor array described above toanerobius, gingivalis, and the control is shown in FIG. 5. Note that thereproducibility of the sensor array was very good. The response (thenormalized resistance change, (R_(max−)R_(o))/R_(o)), where R_(max) andR_(o) are the maximum and base (initial) resistance, respectively) ofthe sensor array to each sample tested is employed to form a covariancematrix, which is used to do principal component analysis. PCA of the twobacteria plus control (data not shown) were clearly discriminated by thesensor array. SIMCA was also used to evaluate the data. The model wasbuilt with all the data as the training set and the data from the firsttest was used as the unknown. A classification rate of 100% was obtainedusing the SIMCA algorithm. KNN was also used to examine the data set. Amodel was built using the data from three sample tubes of each bacteriaplus the control. One of the samples was used as the unknown. Using 3 or5 nearest neighbors in the KNN algorithm gave a classification rate of66%. The FID algorithm was not used on this data set.

In the second phase study, ten samples of 11 bacteria and one funguswere tested. The temperature of the substrates was controlled at 28±0.1°C. for all tests. The sample tubes were not temperatures controlled. Asdescribed in the experimental section, each bacterium was tested 19times among 9 test tubes. Thirty-two sensors responded to 11 bacteriaand one fungus, 19 times for each. A covariance matrix that contained 32columns (one column for each sensor response) and 12×19 rows (bacteriatested at different times) was formed. This matrix was used to doprincipal component analysis.

A different algorithm, Fisher Linear Discrimination, was introduced toprocess the data set. To construct a model using the FLD method, it isrequired that the data take the form of a square matrix. The columns androws in the matrix correspond to the number of sensors and the number oftest samples, respectively. Hence, to use FLD, the number of sensorsneeds to be equal to the number of sample tests. Each of the 11 bacteriaand one fungus were tested 19 times thus, only 19 sensors could be usedto construct the FLD model. Hence, a square matrix was formed using eachof the bacteria tested 19 times and choosing 19 sensors out of the 32.The very first test (tube 1) and the last test (tube 5) of eachbacterium were used as unknowns. The first 19 sensors out of the32-sensor array were found to give the highest prediction rate out ofother sensor combinations. Twenty-four unknowns were predicted from theFLD model. The results provided a classification rate of 91.7% (see,Gibson, T. D., Prosser, O., Hulbert, J. N., Marshall, R. W., Corcoran,P., Lowery, P., Ruck-Keene, E. A., Heron, S., Sensors and Actuators (B)44, 413-422, 1997).

As a comparison, a SIMCA model was built with the same training set usedfor the FLD analysis. The same 24 unknowns was used for SIMCAprediction. The results provided a classification rate of 75%. The KKNalgorithm was also used and the classification rate was 66%.

TABLE 2 SENSOR COMPOSITION AND DEPOSITION CONDITIONS CHIP ENX-1-070798Sensor Dilution P'er # Polymer # Solvent Ratio 19 Hydroxypropylcellulose Sr 1 water 150 to 1 22 Methyl vinyl ether-co-maleic acid,50/50 Sr 2 water 151 to 1 34 Polyacrylamide Sr 3 water 150 to 1 35Polyacrylamide, carboxyl modified (LC) Sr 4 water 150 to 1 36Polyacrylamide, carboxyl modified (HC) Sr 5 water 150 to 1 55Poly(ethylene oxide) Sr 6 water 150 to 1 73 Poly(vinyl alcohol), 100%hydrolyzed Sr 7 water 150 to 1 74 Poly(vinyl alcohol), 98% hydrolyzed Sr8 water 150 to 1 CHIP ENX-2-070798 3 Alginic acid, sodium salt Sr 9toluene  25 to 1 10 Ethylene-co-ethyl acrylate, 82/18 Sr 10 toluene  25to 1 12 Ethylene-co-vinyl acetate, 86/14 Sr 11 toluene  25 to 1 391,2-Polybutadiene Sr 12 toluene  25 to 1 42 Polycaprolactone Sr 13toluene  25 to 1 41 Poly(n-butyl methacrylate) Sr 14 toluene  25 to 1 48Poly(n-ethyl methacrylate) Sr 15 toluene  25 to 1 50 Polyethylene,chlorinated (42 & Cl) Sr 16 toluene  25 to 1 CHIP ENX-3-070798 54Polyethylene, chlorosulfonated Sr 17 toluene  25 to 1 59 Poly(isobutylmethacrylate) Sr 18 toluene  25 to 1 63 Poly(α-methyl styrene) Sr 19toluene  25 to 1 68 Polystyrene Sr 20 toluene  25 to 1 80 Poly(vinylstearate) Sr 21 toluene  25 to 1 87 Styrene/ethylene/butylene, ABA blockSr 22 toluene  25 to 1 95 Vinyl chloride/vinyl acetate/hydroxypropyl Sr23 toluene  25 to 1 79 Poly(vinyl pyrrolidone) Sr 24 water 150 to 1 CHIPENX-4-070798 63 Poly(α-methyl styrene) Sr 25 toluene  25 to 1 79Poly(vinyl pyrrolidone) Sr 26 water 150 to 1 86 Styrene-co-butylmethacrylate Sr 27 toluene  25 to 1 82 Styrene-co-acrylonitryle, 75/25Sr 28 THF 100 to 1 90 Vinyl alcohol-co-vinyl butyral; 20/80 Sr 29 THF100 to 1 104 Poly(4-methoxy styrene) Sr 30 THF 100 to 1 105 Poly methylhydrosiloxane Sr 31 THF 100 to 1 102 Poly diphenoxyphosphazene Sr 32 THF100 to 1 carbon black was used in each sensor at a concentration between20-25 wt %

TABLE 3 LIST OF BACTERIA AND THEIR METABOLIC PRODUCTS BACTERIANOMENCLATURE METABOLIC PRODUCTS OR OFF-GASES Enterobacter cloacae Bac 1Isobutyric and isovaleric acid Cit. Koseri Bac 2 N/A PsuedomonasAeruginosa Bac 3 N/A Veilonella species Bac 4 Acetic and propionic acidand isoamyl alcohol Prevotella melaninogenica Bac 5 Isovaleric acidEscherichia coli Bac 6 Acetic and propionic acid Klebseilla PneumoniaeBac 7 Methyl ethyl ketone, methylbutanal, 2-butanol, pentanone, dimethylsulfide, isobutanol, isopentylacetate, 2-heptanone isopentanol,2-nonanone, 2-undecanone Streptococcus mutans Bac 8 Acetic acid,propionic acid *Candida albicans Bac 9 N/A Prevotella intermedia Bac 10Isovaleric acid Fusobacterium nucleatum Bac 11 Acetic, propionic andbutyric acid Staph. aureus Bac 12 Acetic, 2-butanone, 2-butanol,pentanone, methyl butanol, toluene, 2-heptanone, isopentanol,2-nonanone, 2-undecanone, acetone, 2-nondecagon Peptostreptococcusanerobius Acetic, isobutyric, butyric, isovaleric and isocaproic acidPorphyromonas gingivalis Isovaleric acid *This is a fungus

Example 2

This Example illustrates that the apparatus and methods comprising thesensor arrays of the present invention are suitable for process controlof anesthetic gases.

As disclosed herein, a method for monitoring anesthetic gases in orderto establish reliable monitoring of a patient's condition while underanesthetics is possible.

Conducting-polymer composite sensors change resistance when exposed toan analyte in the vapor phase, and the pattern of such resistancechanges across an array allows identification of a concentration of ananalyte. The pattern height allows identification of the concentrationof an analyte. The experiments show that these arrays are suitable forprocess control over the concentration of anesthetic gases at levelsthat are clinically of interest.

Using a 18-sensor array a suitable concentration of halothane wasdelivered. The flow rate of the carbon dioxide carrier gas was 10mnL/min. The anesthetic gas flow rate was 0.2 mL/min, thus the ratio ofcarrier gas flow over the summation of the carrier gas flow and theanesthetic gas flow was 2%. FIG. 7 illustrates the response of 2%halothane on the sensor array. FIG. 8 illustrates the linear responsefor sensor 10 with halothane concentration.

TABLE 4 18 SENSOR ARRAYS Sensor Polymer and carbon black Carbon black 1.Poly(4-vinyl phenol) [24979-70-2] 40 mg Carbon MW 1500-7000 PolysciencesCat #06527 black 0.160 g in 20 ml THF (soluble in THF) 2.Poly(Styrene-co-alkyl/alcohol) 46 mg carbon Polysciences Cat #03773black 5.7% hydroxyl, MW 1500 (soluble in 0.156 g in 20 ml THF THF) 3.Poly (α-methylstyrene) [25014-31-7] 41 mg carbon Aldrich black 0.164 gin 20 ml THF 4. Poly(vinyl chloride - vinylacetate) [9003-22-9] 39 mgcarbon 10% vinyl acetate black Polysciences Cat #07058 0.164 g in 20 mlTHF 5. Poly(vinyl pyrrolidone) [9003-39-8] 41 mg carbon Aldrich blackAverage Mw 10,000 (both in TFSH @ 6 mg/ml) 0.160 g in 20 ml THF 6.Poly(vinyl acetate) [9003-20-7] 42 mg carbon Polysciences blackMW:500,000 0.163 g in 20 ml 7. Poly(methyl vinyl ether - maleic 39 mgcarbon anhydride) [9011-16-9] black Polysciences Cat #0303 0.162 g in TF8. Poly(bisphenol A carbonate) [24936-68-3] 39 mg carbon MW32,000-36,000 black Polysciences Cat #00962 0.169 g in 20 ml THF 9.Poly(styrene) [9003-53-6] 41 mg carbon MW 125,000-250,000 beads blackPolysciences Cat #00574 0.160 g in THF 10. Poly(styrene - maleicanhydride) [9011-13-6] 40 mg carbon 50% of each Mw 1600 blackPolysciences Cat #0316 0.160 g in 20 ml THF 11. Poly(vinyl butyral)[63148-65-2] 41 mg carbon Mw 100,000-150,000 black Polysciences Cat#06100 0.160 g in 20 ml THF 12. Poly(sulfone) [25135-51-3] 40 mg carbon0.166 g in 20 ml THF black Mw 30,000 Polysciences Cat #07074 13.Poly(methyl methacrylate) [9101-14-7] 41 mg carbon Aldrich black AverageMw˜120,000 Contains <5.0% toulene 0.162 g in 20 ml THF 14.Poly(vinylidene chloride - acrylonetrile) [9010- 40 mg carbon 76-8]black 0.161 g in THF (80:20) Polysciences cat. #09747 15.Poly(caprolactone) [24980-41-4] 42 mg carbon Polysciences cat. #07039black Biodegradable polymer 0.159 g in 20 ml benzene 16. Poly(ethylene -vinyl acetate) [24937-78-8] 39 mg carbon 0.168 g in 20 ml benzene black82% ethylene Polysciences cat. #02309 17. Poly(ethyleneoxide)[25322-68-3] 42 mg carbon Aldrich black Arc Mw 100000 0.162 g in benzene*Sonicated each suspension for 5 min. 18. Poly(9-vinyl carbazole) ˜40 mgcarbon Aldrich [25067-59-3] black 18,260-5 Ave. Mw CQ 1,100,000 0.162 gpolymer

It is understood that the examples and embodiments described herein arefor illustrative purposes only and that various modifications or changeson light thereof will be suggested to persons skilled in the art and areto be included within the spirit and purview of this application andscope of the appended claims. All publications, patents, and patentapplications cited herein are hereby incorporated by reference for allpurposes in their entirety.

What is claimed is:
 1. A method for detecting pneumonia, said methodcomprising: contacting an array of sensors with mammalian breathsuspected of containing a marker gas indicative of pneumonia; anddetecting said marker gases to determine the presence of pneumonia.
 2. Amethod in accordance with claim 1, wherein said array of sensorscomprises a member selected from the group consisting of a surfaceacoustic wave sensor, a quartz microbalance sensor; a conductivecomposite; a chemiresistor; a metal oxide gas sensor and a conductingpolymer sensor, a dye-impregnated polymer film on fiber optic detector,a polymer-coated micromirror, an electrochemical gas detector, achemically sensitive field-effect transistor, a carbon black-polymercomposite, a micro-electro-mechanical system device and amicro-opto-electro-mechanical system device.
 3. A method in accordancewith claim 1, wherein said marker gas is a member selected from thegroup consisting of alkanes, alkenes, alkynes, dienes, alicyclichydrocarbons, arenes, alcohols, ethers, ketones, aldehydes, carbonyls,carbanions, polynuclear aromatics, biomolecules, sugars, isoprenesisoprenoids, VOC, VOA, indoles, skatoles, diarmines, pyridines,picolines, an off-gas of a microorganism and fatty acids.
 4. A method inaccordance with claim 1, further comprising generating a response fromsaid sensors and inputting said response to a neural net trained againstknown marker gases.
 5. A method in accordance with claim 1, furthercomprising concentrating said mammalian breath prior to contacting saidarray of sensors.
 6. A method in accordance with claim 5, wherein saidmammalian breath is concentrated in a breath collector concentrator. 7.A method in accordance with claim 6, wherein said breath collectorconcentrator is adapted to receive breath from the nose, nasal passagesand mouth.
 8. A method in accordance with claim 6, wherein said breathcollector concentrator is adapted to provide breath from the nostril toavoid cross-contamination from the mouth.
 9. A method in accordance withclaim 1, wherein said microorganism is a member selected from the groupconsisting of strep. pneumoniae, mycoplasma, chlamydia pneumoniae, andH. flu.
 10. A method in accordance with claim 1, wherein said mammalianbreath further comprises additional microorganism marker gases.